Man pages for SEMdeep
Structural Equation Modeling with Deep Neural Network and Machine Learning Algorithms
| classificationReport | Prediction evaluation report of a classification model |
| crossValidation | Cross-validation of linear SEM, ML or DNN training models |
| getConnectionWeight | Connection Weight method for neural network variable... |
| getGradientWeight | Gradient Weight method for neural network variable importance |
| getLOCO | Compute variable importance using LOCO values |
| getShapleyR2 | Compute variable importance using Shapley (R2) values |
| getSignificanceTest | Test for the significance of neural network input nodes |
| getVariableImportance | Variable importance for Machine Learning models |
| mapGraph | Map additional variables (nodes) to a graph object |
| nplot | Create a plot for a neural network model |
| predict.DNN | SEM-based out-of-sample prediction using DNN |
| predict.ML | SEM-based out-of-sample prediction using nodewise ML |
| predict.SEM | SEM-based out-of-sample prediction using layer-wise ordering |
| SEMdnn | SEM train with Deep Neural Netwok (DNN) models |
| SEMml | Nodewise SEM train using Machine Learning (ML) |
